The interactive and cumulative effect of temperature and rainfall on land cover change is a priority at global, regional and local scale. This study examined changes in six land cover categories (forestland, grasslands, shrub land, bare land, built-up areas and agricultural lands) in four sub-catchments (Amala, Nyangores, Talek and Sand River), of the Mara River basin over a 30-year period (1987-2017) and made predictions of future land cover change patterns. Landsat Imageries of 90 m resolution were retrieved and analyzed using ArcGIS 10.0 software. Relationship between NDVI, temperature and precipitation was determined using Pearson's correlation coefficient, while Markov chains analyses were performed on different land cover categories to project future trends. Results showed low to moderate (R 2 = 0.002 to 0.6) trends of change in NDVI of different land cover categories across all sub-catchments. The greatest change (R 2 0.34 to 0.5) was recorded in bare land in three of the four sub-catchments studied. Precipitation showed a strong positive correlation with built-up areas, forestlands, croplands, bare land, grasslands and shrub lands, while temperature correlated strongly but negatively with the same land cover categories. The change detection matrix projected significant but varying changes in land cover categories across the four sub-catchments by 2027. This study underscores the impact of changing climatic factors on various land cover categories in the Mara River basin sub-catchments, with different land cover categories exhibiting strong positive sensitivity to high precipitation and low temperature and vice-versa.

Background: The honeybee (Apis mellifera L.) is an important insect that produces honey wax and royal jelly, and propolis that thought to fight infections. It also acts as a cross pollinator of both agricultural and wild plants. However, honeybee colonies are presently faced with a number of constraints both globally and locally. Like in many parts of the world, hive colonization and honey yields in Transmara West Sub-County of Kenya have been on a decline; attributed partly to increased pesticide use. This study thus set out to establish the impacts of pesticides use on honeybee mortality rate and honey production by screening honeybee, honey and pollen for pesticide residues. Methods: A longitudinal descriptive survey and experimental design was adopted for the study. Sixteen apiaries were selected and two strong colonies in Langstroth hives identified in each apiary. These were replicated once to bring the total to 64 colonies, which acted as controls and treatments. Traps were fixed at hive entrances to aid in collection of dead bees at weekly intervals for a period of six months (March to October 2015). Samples of honeybee colony matrices among them pollen loads, honeybee and honey were collected from the identified colonies and analyzed for amitraz, chlorfenvinphos, cypermethrin, deltamethrin and malathion residues using Queshers method at Maseno University chemistry laboratories.Differences in honeybee mortality rate and honey yields between experimental sets were established by one way ANOVA followed by a Turkey HSD post hoc test. A structured questionnaire was also administered to select bee keepers to evaluate their perception on and role in pesticide use. Their responses were analyzed using the χ2 test or Fisher's exact test.Results: Mortality rate in treated colonies (229±5.1) was significantly higher than in control colonies (73±11); MSD=4.6791, p=0.01. Likewise, honey yield in control colonies (16.0±1.0 kg) was significantly higher than in treated colonies (8.7±1.2 kg); (MSD=4.8425, p=0.024). For instance, the average season one honey yield in the control colonies was 18.0 ± 1.0 kg compared to 7.1 ±1.10 kg, 8.4 ±1.50 and 9.2 ±1.7 kg, in treated colonies. This implies that increased pesticide use may have contributed to increased honeybee mortality rate and reduced honey yields. No residues were detected in all honeybee colony matrices, implying that honeybee products within the study settings were safe for consumption. Majority of farmers reported observing changes in honeybee colony strength, a reduction in honey yields, reduced colony size, significantly weakening the colonies.Conclusion: This study established an inverse relationship between pesticides use honeybee mortality rate, with significant increase in mortality rate and reduced honey production being associated with its use. Absence of residues in the matrices in all the studied sites suggests honeybee products from the study setting are still safe for human consumption. Nevertheless, farmers need to be trained on safe handling of pesticides. In addition, there is need for further research on the synergistic impacts of pesticides use on honeybees, and the need for alternative and ecofriendly pest control options to curb the challenge associated with indiscriminate effects of pesticides on other important insects like honeybees.